Using Data to Manage Urban Dynamics
While a Democracy can be defined as a societal structure governed by the people, a Datacracy is one governed by the algorithms that have collected data from the people. A society based on Datacracy is one managed by algorithms that, through crowdsourced technologies and biometric recognition systems, quantify the best outcomes for the overall society. Together with Big Data, the gathered data is used either to assess the participation of each citizen or to data-mine a whole city as a means to convert it into a transparent platform visible to the eyes of the public.
Post 9/11 and The Brave New World
The year 2001 foreshadowed the decades to come. With the normalization of surveillance systems, it presented to the world the most reliable enemy against terrorism: data.
On 11th September 2001, the world witnessed one of the most impactful episodes in terms of a nation’s security breach. At that time, airport security was limited to passport control and with luck, a luggage scan. Many governments weren’t used — yet quite tempted — to employ precise and interconnected surveillance cameras throughout their cities, nor technological advances that allow for authentication and identification to receive their deserved attention.
The world needed a call to action.
“I certainly hope that we never go through another 9/11, but if we do, it’s good to know that there will be better technology to deal with the cataclysm.”
Thereafter, the UK became the catalyst of change and its time-honored CCTV system was later adopted in many places globally. Labs and technological research institutes received incentives to accelerate the implementation of innovative surveillance technologies. The internet offered its free access protocol to establish a framework where police bodies could use it for crowd control and centralize urban gathered data.
The Millennial Rise and Surveillance Distrust
Cameras now record everyone. Along with the application of CCTV systems — initially accessible only to governments and private companies — the curve of technological adoption jumped exponentially. Mobile devices started, for instance, to be set up with cameras and with time, biometric recognition systems. The prices decreased and mobile technology reached even the most impoverished social fabrics. This fast rate of adoption and normalization made the development of smart devices grow in importance and the assimilation of wearable and even implantable sensors ever more popular among young generations and tech enthusiasts, including the baby-boomers.
“An alternative modernity worthy of the name would recover the mediating power of ethics and aesthetics. This would be accomplished not by a return to blind traditionalism but through the democratization of technically mediated institutions.”
— Andrew Feenberg, Between Reason and Experience: Essays in Technology and Modernity.
The next decade introduced novel models of technology usage. Social media platforms were introduced and embraced, later acting for some as extensions of peoples’ identities. Artificial Intelligence helped move machine vision applications forward, capturing and identifying body motions seamlessly and more precisely. The internet turned into an essential part of many lives on Earth, making large distances seemingly fictitious and enabling people to inhabit multiple virtual environments.
Yet, together with the many innovative changes enabled by technological developments, shifts in surveillance interests came about as well. At some point, CCTV cameras weren’t enough to monitor the life of the city dwellers. As people inhabited other layers enabled by digitalization, it became clear that it was not only criminal and terrorist activities that were under the scrutiny of governments and corporations. The way people interact and think online became the focus of attention for companies and even political parties; data became the most cherished good.
Data mining increased, sometimes operating in places most users were unaware of. Personal data was collected via cookies and cloud databases that store information gathered from social media. Ongoing data leak cases, such as Cambridge Analytica’s data mining event, made surveillance technologies once awaited and demanded by the public shift from useful tools to weapons that incite general distrust.
“Cambridge Analytica […] reportedly tapped the information to build psychographic profiles of users and their friends, which were used for targeted political ads in the UK’s Brexit referendum campaign, as well as by Trump’s team during the 2016 US election.”
— Ian Sherr.
Pandemic vs. Data
The increased emphasis placed on surveillance technologies to ensure the safety and wellbeing of the population soon prompted a general fear of being continuously watched. Often poorly accountable in terms of legitimacy, data-mining cases such as the Snowden episode, evoked among a large portion of the population scenarios alike to science-fiction narratives such as “1984” by George Orwell. Countries such as China became preeminent in employing pervasive surveillance technologies and were seen by some as the primary factor responsible for eroding the personal privacy of Chinese citizens. Still, such practices have been influential worldwide and have been adopted by other governments to maintain the safety and the order of the country as a whole.
“The United States and other countries use some of the same techniques to track terrorists or drug lords. Chinese cities want to use them to track everybody.”
— Paul Mozur and Aaron Krolik.
Despite the growing distrust of surveillance technologies, current events that foment a global response are the ones acting as catalyzers for change. Almost two decades after September 11th, the world is facing a global crisis involving a pandemic that has caused the death of millions and months of lockdown in many places on Earth. Still without a cure, the world has embarked on an “arms race” to find a vaccine and solutions to unlock people from their homes and return them to the lives they once had. In an effort to continue with “business as usual”, companies have relocated their offices to online platforms, delivery apps have proliferated dramatically, and virtual reality technologies are being adopted in new ways. Data has once again been brought back to the main stage.
China, which was publicly criticized for exploiting its citizens’ data, is now the accelerator of monitoring technologies that are helping contain the spread of COVID-19. From sharing algorithms that hasten the detection and testing of coronavirus, the elaboration of predictive and early warning systems powered by Big Data that informs the population nationwide about the pandemic situation, to sensors that map and track individuals supposedly infected, China has successfully implemented many data-driven tools in the current fight against a systemic global burden.
“Revolution will not be televised.” Is that so?
As if 2020 was the year picked to portray the illusions of dystopian worlds pictured by science fiction, a pandemic crisis is not enough to display such a scenario. As more emerging technological solutions are made available to the public, the more they use them in their own interests as well. Recent popular uprisings make use of mobile data networks to increase strategic coordination among people and to make visible cases where the omnipresent eye of surveillance tends to fail. With online platforms that enable sharing videos in real-time services, it is not only CCTV systems that hold the power to expose instances where criminal activity is occurring. People now have the power to turn the cameras on governments too.
“May 25, 2020, George Floyd, a 46-year-old African American man, dies after a white Minneapolis police officer pins him to the ground with his knee on Floyd’s neck. A video of the incident is widely shared on social media.”
— Black Lives Matter Live Report on Aljazeera News.
While data is undoubtedly the driver of many changes, it often does not adequately represent the contexts in which they happen. Humans are inclined to shift their needs according to their surrounding circumstances, and it seems, over the years, data has shifted to become a way for the general population to empower themselves. It certainly sheds doubt on how data is managed by governments and institutions but the preceding examples show how populations can benefit, instead of being subject to decisions taken without their participation. Datacracy, in this sense, furthers the possibility that decisions could be made according to facts instead of emotions and biases.
What lies ahead are the possibilities a datacratic system can offer us, including both challenges and opportunities.
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